scholarly journals Pragmatic precision oncology: the secondary uses of clinical tumor molecular profiling

2016 ◽  
Vol 23 (4) ◽  
pp. 773-776 ◽  
Author(s):  
Matthew J Rioth ◽  
Ramya Thota ◽  
David B Staggs ◽  
Douglas B Johnson ◽  
Jeremy L Warner
Keyword(s):  
Science Research ◽  
Molecular Profiling ◽  
Molecular Profile ◽  
Data Repository ◽  
Precision Oncology ◽  
Profile Data ◽  
Secondary Use ◽  
Discovery Science ◽  
Real Time Database ◽  
One Year

Abstract Background Precision oncology increasingly utilizes molecular profiling of tumors to determine treatment decisions with targeted therapeutics. The molecular profiling data is valuable in the treatment of individual patients as well as for multiple secondary uses. Objective To automatically parse, categorize, and aggregate clinical molecular profile data generated during cancer care as well as use this data to address multiple secondary use cases. Methods A system to parse, categorize and aggregate molecular profile data was created. A naÿve Bayesian classifier categorized results according to clinical groups. The accuracy of these systems were validated against a published expertly-curated subset of molecular profiling data. Results Following one year of operation, 819 samples have been accurately parsed and categorized to generate a data repository of 10,620 genetic variants. The database has been used for operational, clinical trial, and discovery science research. Conclusions A real-time database of molecular profiling data is a pragmatic solution to several knowledge management problems in the practice and science of precision oncology.

scholarly journals Rethinking Data Sharing and Human Participant Protection in Social Science Research: Applications from the Qualitative Realm

2017 ◽  
Author(s):  
Dessi Kirilova ◽  
Sebastian Karcher
Keyword(s):  
Data Sharing ◽  
Qualitative Data ◽  
Social Science Research ◽  
Science Research ◽  
Data Repository ◽  
Management Options ◽  
Secondary Use ◽  
Access Controls ◽  
Human Participant ◽  
Human Participants

While data sharing is becoming increasingly common in quantitative social inquiry, qualitative data are rarely shared. One factor inhibiting data sharing is a concern about human participant protections and privacy. Protecting the confidentiality and safety of research participants is a concern for both quantitative and qualitative researchers, but it raises specific concerns within the epistemic context of qualitative research. Thus, the applicability of emerging protection models from the quantitative realm must be carefully evaluated for application to the qualitative realm. At the same time, qualitative scholars already employ a variety of strategies for human-participant protection implicitly or informally during the research process.In this practice paper, we assess available strategies for protecting human participants and how they can be deployed. We describe a spectrum of possible data management options, such as anonymization and applying access controls, including some already employed by the Qualitative Data Repository (QDR) in tandem with its pilot depositors. Throughout the discussion, we consider the tension between modifying data or restricting access to them, and retaining their analytic value. We argue that developing explicit guidelines for sharing qualitative data generated through interaction with humans will allow scholars to address privacy concerns and increase the secondary use of their data.

scholarly journals Explore the Rare—Molecular Identification and Wine Evaluation of Two Autochthonous Greek Varieties: “Karnachalades” and “Bogialamades”

Plants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1556
Author(s):  
Dimitrios Evangelos Miliordos ◽  
Georgios Merkouropoulos ◽  
Charikleia Kogkou ◽  
Spyridon Arseniou ◽  
Anastasios Alatzas ◽  
...  
Keyword(s):  
Molecular Data ◽  
Molecular Profiling ◽  
Scientific Data ◽  
Financial Impact ◽  
Molecular Profile ◽  
Red Wines ◽  
Grape Berries ◽  
Quality Aspects ◽  
Commercial Vineyard ◽  
Of Greece

Wines produced from autochthonous Vitis vinifera varieties have an essential financial impact on the national economy of Greece. However, scientific data regarding characteristics and quality aspects of these wines is extremely limited. The aim of the current study is to define the molecular profile and to describe chemical and sensory characteristics of the wines produced by two autochthonous red grapevine varieties—“Karnachalades” and “Bogialamades”—grown in the wider area of Soufli (Thrace, Greece). We used seven microsatellites to define the molecular profile of the two varieties, and then we compared their profile to similar molecular data from other autochthonous as well as international varieties. Grape berries were harvested at optimum technological maturity from a commercial vineyard for two consecutive vintages (2017–2018) and vilification was performed using a common vinification protocol: the 2017 vintage provided wines, from both varieties, with greater rates of phenolics and anthocyanins than 2018, whereas regarding the sensory analysis, “Bogialamades” wine provided a richer profile than “Karnachalades”. To our knowledge, this is the first study that couples both molecular profiling and exploration of the enological potential of the rare Greek varieties “Karnachalades” and “Bogialamades”; they represent two promising varieties for the production of red wines in the historic region of Thrace.

scholarly journals A computational method for prioritizing targeted therapies in precision oncology: performance analysis in the SHIVA01 trial

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Istvan Petak ◽  
Maud Kamal ◽  
Anna Dirner ◽  
Ivan Bieche ◽  
Robert Doczi ◽  
...  
Keyword(s):  
Clinical Benefit ◽  
Progressive Disease ◽  
Genetic Alterations ◽  
Outcome Data ◽  
Computational Method ◽  
Molecular Profile ◽  
Precision Oncology ◽  
Driver Genes ◽  
Oncology Clinical Trial ◽  
Molecularly Targeted Agents

AbstractPrecision oncology is currently based on pairing molecularly targeted agents (MTA) to predefined single driver genes or biomarkers. Each tumor harbors a combination of a large number of potential genetic alterations of multiple driver genes in a complex system that limits the potential of this approach. We have developed an artificial intelligence (AI)-assisted computational method, the digital drug-assignment (DDA) system, to prioritize potential MTAs for each cancer patient based on the complex individual molecular profile of their tumor. We analyzed the clinical benefit of the DDA system on the molecular and clinical outcome data of patients treated in the SHIVA01 precision oncology clinical trial with MTAs matched to individual genetic alterations or biomarkers of their tumor. We found that the DDA score assigned to MTAs was significantly higher in patients experiencing disease control than in patients with progressive disease (1523 versus 580, P = 0.037). The median PFS was also significantly longer in patients receiving MTAs with high (1000+ <) than with low (<0) DDA scores (3.95 versus 1.95 months, P = 0.044). Our results indicate that AI-based systems, like DDA, are promising new tools for oncologists to improve the clinical benefit of precision oncology.

13P Incidental germline findings from tumor molecular profiling for precision oncology: Is it common and how to manage?

2021 ◽  
Vol 32 ◽  
pp. S1349-S1350
Author(s):  
M. Ivanov ◽  
A. Lebedeva ◽  
D. Seriak ◽  
E. Rozhavskaya ◽  
M. Sharova ◽  
...  
Keyword(s):  
Molecular Profiling ◽  
Precision Oncology

Experience of using the drug Glutoxim in patients with benign and borderline epithelial ovarian tumors after performing conservative surgical treatment

2018 ◽  
pp. 79-86
Author(s):  
A.A. Sukhanova ◽  
◽  
M.Yu. Yegorov ◽  
Keyword(s):  
Surgical Treatment ◽  
High Risk ◽  
Ovarian Tumors ◽  
Molecular Profile ◽  
Control Group ◽  
Profile Data ◽  
Ki 67 ◽  
Risk Of Recurrence ◽  
Relapse Therapy ◽  
E Cadherin

The objective: to increase the effectiveness of treatment of patients with benign and borderline epithelial ovarian tumors (EOT) after conservative operations performed based on the definition of a high risk group for recurrence and malignancy according to the molecular expression profile of the markers p53, Ki-67, estrogen receptors (ER), CD34 and E-cadherin and inclusion in the complex anti-relapse therapy of the immunomodulating drug Glutoxim. Materials and methods. A clinical examination of 60 patients of reproductive age with EOT was performed, which were treated with organ-sparing surgical treatment (main group). Of these 60 patients, 30 women (subgroup I) were diagnosed with benign EOT (BEOT), the remaining 30 women (subgroup II) were diagnosed with borderline EOT (BoEOT) Ia and Ib stages in FIGO. In removed tumors after routine histopathological examination, the molecular profile was determined by immunohistochemically determining the protein regulator of apoptosis p53, proliferation index (PI) by Ki-67 expression, estrogen receptors — ER, microvessel density by CD34 expression and E-cadherin intercellular adhesion protein. Based on the molecular profile determination data, the removed tumor was ranked as high or low risk of recurrence and malignancy. Patients from the high-risk group for relapse and malignancy according to the molecular profile data included the immunomodulating drug Glutoxim in the complex anti-relapse therapy - intramuscularly 10 mg daily for 2 weeks with a course repeated every six months for 3 years. The control group consisted of 64 patients with BEOT and BoEOT, who underwent conservative surgical treatment without further anti-relapse treatment. Results. During the molecular profile study, it was found that high risk of recurrence and malignancy had EOT with p53 expression (LI ≥15%), high proliferative activity of cells with Ki-67 expression (PI ≥10%), low estrogen reception (LI ER < 49.5%), high density of microvessels on the expression of CD34 (IM ≥40 mv /mm2), low level of intercellular adhesion on the expression of E-cadherin (LI <59%). Molecular profile characterizing a high risk of recurrence and malignancy, in most cases was inherent in BoEOT. The purpose of a comprehensive anti-relapse treatment with the inclusion of the immunomodulatory drug Glutoxim (intramuscularly daily at 10 mg for 2 weeks) after performing of sparing conservative surgical treatment with a repetition of the course every six months in patients at high risk of relapse and malignancy according to molecular profile data has reduced the relapse of EOT to 6.7% in patients of the main group compared with 20.3% in the control group during three years of follow-up observation of patients. The difference is statistically significant (p <0.05). Conclusion. In order to prevent cases of recurrence and malignancy in patients with EOT at high risk of relapse and malignancy according to molecular profile data after a sparing surgical treatment that preserves their reproductive function, it is recommended that Glutoxim is administered in complex anti-relapse therapy at 10 mg intramuscularly per every day for 2 weeks with a repetition of the course every six months for 3 years. Key words: benign epithelial ovarian tumors, borderline epithelial ovarian tumors, high risks of recurrence and malignancy, anti-relapse therapy, reproductive function, Glutoxim.

scholarly journals Incidental germline findings during molecular profiling of tumor tissues for precision oncology: molecular survey and methodological obstacles

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Alexandra Lebedeva ◽  
Yulia Shaykhutdinova ◽  
Daria Seriak ◽  
Ekaterina Ignatova ◽  
Ekaterina Rozhavskaya ◽  
...  
Keyword(s):  
Normal Tissue ◽  
Sanger Sequencing ◽  
Computational Prediction ◽  
Bioinformatic Analysis ◽  
Molecular Profiling ◽  
Precision Oncology ◽  
Germline Variants ◽  
Manual Curation ◽  
Uncertain Significance ◽  
Tumor Types

Abstract Background A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized. Methods Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP. Results Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes). Conclusion Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.

scholarly journals Investigating the clinical, pathological and molecular profile of oncocytic adrenocortical neoplasms

2021 ◽  
Author(s):  
Eleanor Fewings ◽  
Serena Khoo Sert Kim ◽  
Alexey Larionov ◽  
Alison Marker ◽  
Olivier Giger ◽  
...  
Keyword(s):  
Treatment Strategies ◽  
Case Series ◽  
Missense Variant ◽  
Molecular Profiling ◽  
The Cancer Genome Atlas ◽  
Biological Behavior ◽  
Molecular Profile ◽  
Mutation Burden ◽  
Rare Tumours ◽  
Paired Tumour

Background: Malignant oncocytic adrenocortical neoplasms (OANs) are rare tumours with a distinctive biological behavior compared to conventional adrenocortical carcinoma (ACC). The current prognostic systems overestimate the malignant potential of these tumours and guidance for surveillance and treatment strategies are lacking. Aim: To evaluate the utility of clinical, pathological and molecular markers in predicting the biological behavior and outcomes of malignant OANs. Methods: A retrospective clinicopathological review of ten histologically confirmed OANs was carried out. Whole exome sequencing (WES) of germline and paired tumour samples was performed for four of the ten OAN cases and compared to WES data from five cases of conventional ACC and data from The Cancer Genome Atlas (TCGA). We reviewed all cases of malignant OAN reported in the literature and compared to our case series. Results: Eight (80%) tumours were classified as malignant, one borderline and one benign (Lin-Weiss-Bisceglia criteria: LWB). The malignant OAN were larger tumours and had higher MIB index and Helsinki scores. Molecular profiling identified a pathogenic germline variant in MSH6 in an individual in the OAN group. The OAN samples had a lower mutation burden compared to the ACC samples. Somatic driver variants were identified in OAN and ACC samples including a pathogenic missense variant in CTNNB1. Conclusion: In this study, the LWB classification demonstrated sensitivity for the differentiation of benign from malignant OAN. Molecular profiling identified dysregulation in DNA repair and Wnt signaling pathways in both OAN and ACC samples, suggesting a molecular overlap between OAN and conventional ACC.

scholarly journals MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

2010 ◽  
Vol 11 (1) ◽  
Author(s):  
Tomáš Pluskal ◽  
Sandra Castillo ◽  
Alejandro Villar-Briones ◽  
Matej Orešič
Keyword(s):  
Mass Spectrometry ◽  
Molecular Profile ◽  
Profile Data ◽  
Modular Framework

Analysis of molecular profile data using generative and discriminative methods

2000 ◽  
Vol 4 (2) ◽  
pp. 109-126 ◽  
Author(s):  
E. J. Moler ◽  
M. L. Chow ◽  
I. S. Mian
Keyword(s):  
Graphical Models ◽  
Biological Networks ◽  
Domain Knowledge ◽  
Colon Adenocarcinoma ◽  
Comparative Sequence Analysis ◽  
Diagnostic Tools ◽  
Molecular Profile ◽  
Support Vector ◽  
Marker Genes ◽  
Profile Data

A modular framework is proposed for modeling and understanding the relationships between molecular profile data and other domain knowledge using a combination of generative (here, graphical models) and discriminative [Support Vector Machines (SVMs)] methods. As illustration, naive Bayes models, simple graphical models, and SVMs were applied to published transcription profile data for 1,988 genes in 62 colon adenocarcinoma tissue specimens labeled as tumor or nontumor. These unsupervised and supervised learning methods identified three classes or subtypes of specimens, assigned tumor or nontumor labels to new specimens and detected six potentially mislabeled specimens. The probability parameters of the three classes were utilized to develop a novel gene relevance, ranking, and selection method. SVMs trained to discriminate nontumor from tumor specimens using only the 50–200 top-ranked genes had the same or better generalization performance than the full repertoire of 1,988 genes. Approximately 90 marker genes were pinpointed for use in understanding the basic biology of colon adenocarcinoma, defining targets for therapeutic intervention and developing diagnostic tools. These potential markers highlight the importance of tissue biology in the etiology of cancer. Comparative analysis of molecular profile data is proposed as a mechanism for predicting the physiological function of genes in instances when comparative sequence analysis proves uninformative, such as with human and yeast translationally controlled tumour protein. Graphical models and SVMs hold promise as the foundations for developing decision support systems for diagnosis, prognosis, and monitoring as well as inferring biological networks.

scholarly journals Are the biomedical sciences ready for synthetic biology?

2020 ◽  
Vol 11 (1) ◽  
pp. 23-31
Author(s):  
Maxwell S. DeNies ◽  
Allen P. Liu ◽  
Santiago Schnell
Keyword(s):  
Synthetic Biology ◽  
Biomedical Research ◽  
Molecular Level ◽  
Biological Systems ◽  
Science Research ◽  
Functional System ◽  
Biomedical Sciences ◽  
Present Evidence ◽  
Experimental Control ◽  
Discovery Science

AbstractThe ability to construct a functional system from its individual components is foundational to understanding how it works. Synthetic biology is a broad field that draws from principles of engineering and computer science to create new biological systems or parts with novel function. While this has drawn well-deserved acclaim within the biotechnology community, application of synthetic biology methodologies to study biological systems has potential to fundamentally change how biomedical research is conducted by providing researchers with improved experimental control. While the concepts behind synthetic biology are not new, we present evidence supporting why the current research environment is conducive for integration of synthetic biology approaches within biomedical research. In this perspective we explore the idea of synthetic biology as a discovery science research tool and provide examples of both top-down and bottom-up approaches that have already been used to answer important physiology questions at both the organismal and molecular level.

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